Open AccessReview on circular-linear regression models
Author(s) -
Hanin Hazwani Mohammad,
Siti Zanariah Satari,
Wan Nur Syahidah Wan Yusoff
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1988/1/012108
Subject(s) - linear regression , regression analysis , inference , linear model , statistical inference , statistics , regression , mathematics , general linear model , variable (mathematics) , econometrics , computer science , artificial intelligence , mathematical analysis
Classical linear statistics method is no longer appropriate when handling circular data since the data is influenced by direction or angle. Considering the possibility of circular data appeared as dependent variable, it has resulted in the remodeling of classic linear regression model into circular-linear regression model over the past few decades. It is important to acknowledge these circular data characteristics as it can affect the descriptive and inference of statistical analysis. With the growing body of literature regarding this issue, this paper will review on circular-linear regression model by highlighting and exploring their benefits and limitations.